The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find a dataset script at /src/services/worker/msu-ceco/agxqa_v1/agxqa_v1.py or any data file in the same directory. Couldn't find 'msu-ceco/agxqa_v1' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/msu-ceco/agxqa_v1@851e2979528b70f0d1c3ffaabe4bb17ffaadac42/agxqa-train-2024-06-11.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 72, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1906, in dataset_module_factory
                  raise FileNotFoundError(
              FileNotFoundError: Couldn't find a dataset script at /src/services/worker/msu-ceco/agxqa_v1/agxqa_v1.py or any data file in the same directory. Couldn't find 'msu-ceco/agxqa_v1' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/msu-ceco/agxqa_v1@851e2979528b70f0d1c3ffaabe4bb17ffaadac42/agxqa-train-2024-06-11.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']

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DISCLAIMER: DUE TO AN ONGOING PUBLICATION REVIEW FOR ITS ASSOCIATED JOURNAL PAPER, THIS REPO IS CURRENTLY EMPTY. THE REST OF THE DATA WILL BE UPLOADED UPON THE PAPER ACCEPTANCE.

Dataset Card for AgXQA 1.1

Dataset Summary

The Agricultural eXtension Question Answering Dataset (AgXQA 1.1) is a small-scale, SQuAD-like QA dataset targeting the Agriculture Extension domain. Version 1.1 currently contains 2.1K+ questions related to irrigation topics across the US, with a focus on the Midwest since our crops of interest were mainly soybean and corn.

Supported Tasks and Leaderboards

Question Answering.

Languages

English (en).

Dataset Structure

Data Instances

agxqa_v1

An example from the 'test' split looks as follows.

Please note that the "context" of this example was too long and was cropped:

{
    "answers": {
        "answer_start": [78, 21],
        "text": [' the rate water can enter the soils surface', 'the quantity of water that can enter the soil in a specified time interval']
    },
    "context": "Irrigation Fact Sheet # 2: Instantaneous Rates. The soils infiltration rate is the rate water can enter the soils surface. Michigan soils...",
    "id": "1170477",
    "question": "what is infiltration rate?",
    "category": "Irrigation",
    "references": "Kelley, L. (2007a). Irrigation Fact Sheet # 2 - Irrigation Application Instantaneous Rates. https://www.canr.msu.edu/uploads/235/67987/FactSheets/2_IrrigationApplicationRates1.30.pdf",
}

Data agxqa_v1

The data fields are the same among all splits.

agxqa_v1

  • id: a string feature.
  • category: a string feature.
  • context: a string feature.
  • question: a string feature.
  • answers: a dictionary feature containing:
    • text: a string feature.
    • answer_start: a int32 feature.
  • references: a string feature.

Data Splits

name train validation test
agxqa_v1 1503 353 330

Dataset Creation

Curation Rationale

The creation of this dataset aims to enhance the performance of NLP models (e.g., LLMs) in understanding and extracting relevant information about agro-hydrological practices for crops such as corn and soybeans.

Scope and Domain

The dataset specifically focuses on irrigation practices, techniques, and related agricultural knowledge concerning corn and soybeans. This includes, but is not limited to:

  • irrigation laws and policies
  • irrigation methods (e.g., drip, sprinkler, furrow),
  • irrigation scheduling,
  • soil moisture monitoring,
  • crop growth stage,
  • crop water requirements,
  • general crop (soybean and corn) characteristics

Source Data

Initial Data Collection and Normalization

About ~600 paragraphs (e.g., context) were extracted from the Agriculture Extension Corpus (AEC1.1). For more details about AEC1.1's data sources, please refer to its dataset card here.

Who are the source language producers?

  • CECO curated and supervised the creation and annotations of the QA pairs.
  • Regarding the original paragraphs/contexts, please see here.

Annotations

Annotation process

We followed the general guidelines described in Rajpurkar et al. (2016), which also inspired us to create a SQUAD-like dataset. We leveraged Deepset's annotation tool to annotate the paragraphs and create the QA pairs.

Our main guidelines can be summarized as follows:

  • Question formulation: Based on the rationale in the paragraph, the extracted questions represented common queries by farmers and agricultural practitioners regarding irrigation.
  • Answer collection: Already present in the paragraph, so the annotations cover both short and long:
    • clauses
    • subjects
    • predicates
    • phrases (nouns, verbs, adjectives and adverbials)
  • Quality control: Domain experts reviewed and validated the QA pairs to ensure accuracy and relevance. This review was conducted weekly on 50% of the annotated batch (randomly selected) for that week.
  • Diversity and Coverage: Since the crops of interest (soybean and corn) are mostly grown in the Midwest states of the USA, most of the QA pairs cover those states. However, the dataset also includes general irrigation QA pairs, that are applicable in most states.
  • Ethical considerations: To maintain transparency and credibility, we cited the original authors of the annotated paragraphs for each QA pair. Please see the annotated example provided above.

For more information on the annotation process, please refer to here (TO_DO).

Who are the annotators?

There were three annotators in total, two with a background in agricultural topics. Two experts in water and irrigation research hired them and supervised their annotations.

Personal and Sensitive Information

  • Some of the original paragraphs contained extension educators' names and email addresses, but these have been analyzed accordingly. In other words, they have been replaced with x 's in our dataset.
  • For each paragraph, we referenced the main article, where the context was extracted.

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

  • Version 1.1 is small and only contains irrigation-related topics, so we suggested not using it in production since, in the real world, agriculture-based questions require temporal and geospatial information, which is not covered yet.
  • We found three paragraphs that contained URLs (links to an Extension YouTube video and a decision support tool). These are outliers and do not necessarily provide implicit answers. They will be removed in version 2.

Other Known Limitations

More Information Needed

Additional Information

Licensing Information

The dataset is distributed under the [TO-DO] license.

Citation Information

[TO-DO]

Contributions

[More Information Needed]

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